1344 Trends in Applied Econometrics Software Development 1985–2008
simulation module to generate bootstrap draws.” If the inference is simulation-
based, one also needs diagnostics on the efficacy and reliability of the associated
simulation methods.
User interfaces will have to be updated. Following Google and Gretl, users
will expect econometric software to deal with labels and numbers in their native
language and application menus to use their own character sets. The graphical
interface will also need reconstruction as customers adapt to modern graphical
interfaces. New interfaces will help to make better use of the many options that
programs and procedures have, both on the user’s own computer and on inter-
net archives. Many procedures are ineffective because they are hard to find in the
current menu structures. Based on a user history, the menus will “automatically”
select the best options for the user.
The market for specific econometric software is too small for one program to
keep up with all recent scientific developments in econometrics, mathematics and
statistics, to keep advanced knowledgeable customers interested in buying updates,
and to implement lessons from human–computer interaction (HCI) research to
keep attracting new customers.
The presence of trends implies some predictability of future developments. The
pattern that has emerged in the last 25 years does not make it likely that new, fully-
fledged, dedicated econometric software packages with high academic standards
are going to be developed. Academic returns on high-quality, robust, versatile,
and well-documented and supported econometric software development are low.
Changing citation practices for software use, as exemplified by theJAEdata and
code archive, may increase these returns in the years ahead.
In this chapter I have discussed over 20 years of changing software use and soft-
ware development for innovative applied econometrics. An increasing range of
software has became relevant in this period. I also classified this large collection
of programs and assessed the continuity of their use. Finally, I pointed out new
direction for econometric modeling software development.
Acknowledgments
I would like to thank Christopher Baum, Jurgen Doornik, Bill Rising, Ronald Schoenberg and
Christian Kleiber for helpful comments on this chapter. All errors are my own.
Note
- Software: I used MS Excel 2000, Windows XP, 5.1 Service Pack 2, MikTeX 2.4, OxEdit 5.0,
Firefox 3, OxMetrics 5.0, GAUSS 7, R 2.7, Google, Google Scholar, Google Books, JSTOR
and Wiley Interscience to prepare this chapter.
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